Submission¶

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [1]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px
import pandas as pd

init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [2]:
#load data
df = px.data.gapminder()
df.head()
Out[2]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:¶

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [3]:
# YOUR CODE HERE
df_2007 = df.query('year==2007')
df_2007_new = df_2007.groupby('continent').sum()
fig = px.bar(df_2007_new, x="pop", y=df_2007_new.index, color=df_2007_new.index, orientation='h')
fig.show()

Question 2:¶

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [4]:
# YOUR CODE HERE
fig = px.bar(df_2007_new, x="pop", y=df_2007_new.index, color=df_2007_new.index, orientation='h')
fig = fig.update_yaxes(categoryorder = 'total ascending')
fig.show()

Question 3:¶

Add text to each bar that represents the population

In [5]:
# YOUR CODE HERE
fig = px.bar(df_2007_new, x="pop", y=df_2007_new.index, color=df_2007_new.index, orientation='h', text_auto= True)
fig = fig.update_yaxes(categoryorder = 'total ascending')
fig.show()

Question 4:¶

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [6]:
df.head()
Out[6]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4
In [7]:
df_new = df.groupby(['year','continent']).sum().reset_index()
#df_new = df.set_index(['continent'])
df_new.head()
Out[7]:
year continent lifeExp pop gdpPercap iso_num
0 1952 Africa 2035.046 237640501 65133.768223 23859
1 1952 Americas 1331.996 345152446 101976.563805 9843
2 1952 Asia 1528.375 1395357351 171450.972133 13354
3 1952 Europe 1932.255 418120846 169831.723043 12829
4 1952 Oceania 138.510 10686006 20596.171300 590
In [8]:
# YOUR CODE HERE
fig = px.bar(df_new, x='pop', y='continent', color='continent', 
             animation_frame='year', range_x=[0, 4000000000])
fig = fig.update_yaxes(categoryorder = 'total ascending')

fig.show()

Question 5:¶

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [9]:
# YOUR CODE HERE
df_country = df.groupby(['year','country']).sum().reset_index()

fig = px.bar(df_country, x='pop', y='country', color='country', 
             animation_frame='year', range_x=[0, 1500000000])
             
fig = fig.update_yaxes(categoryorder = 'total ascending')
fig = fig.update_layout(showlegend=False)
fig.show()

Question 6:¶

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [12]:
# YOUR CODE HERE
fig = px.bar(df_country, x='pop', y='country', color='country', 
             animation_frame='year', range_x=[0, 1500000000], height=1000)

fig = fig.update_yaxes(categoryorder = 'total ascending')
fig = fig.update_layout(showlegend=False)
fig.show()

Question 7:¶

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [13]:
# YOUR CODE HERE
fig = px.bar(df_country, x='pop', y='country', color='country', 
             animation_frame='year', range_x=[0, 1500000000], range_y=[132, 142])

#set the figure
fig = fig.update_yaxes(categoryorder = 'total ascending')
fig = fig.update_layout(showlegend=False)
fig.show()
In [ ]:
 
In [ ]:
 
In [ ]:
 
In [ ]: